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OBJECTIVE: The purpose of this study was to investigate the validity of established insulin resistance indexes, based on fasting blood parameters, in a stable renal transplant population. RESEARCH DESIGN AND METHODS: Fasting insulin, homeostasis model assessment (HOMA), the quantitative insulin sensitivity check index (QUICKI), and McAuley's index were assessed for correlation and agreement with whole-body glucose uptake (M value) divided by prevailing serum insulin concentrations (I value) assessed during a hyperinsulinemic-euglycemic clamp in 51 stable renal transplant recipients, who were at a median of 7.5 years after transplant. Multivariate linear regression analyses were used to determine independent risk factors for insulin resistance. RESULTS: The M/I value correlated with fasting insulin concentration (r = -0.56), HOMA (r = -0.53), QUICKI (r = 0.52), and McAuley's index (r = 0.61) (all P < 0.01). Linear regression showed agreement between all indexes and insulin resistance. However, McAuley's index showed the strongest agreement irrespective of age, sex, renal allograft function, and obesity. In multivariate analysis, fasting insulin concentration (beta = -0.59, P = 0.002), fasting triglyceride concentration (beta = -0.33, P = 0.04), and BMI (beta = -1.22, P = 0.05) were independently associated with the M/I value. CONCLUSIONS: All investigated insulin resistance indexes were valid estimates of insulin resistance in the long-term stable renal transplant population. However, correlation and agreement were strongest for McAuley's index. In addition to fasting insulin and triglyceride concentrations, of which McAuley's index is composed, only BMI seemed to be independently associated with insulin resistance in this population.

Original publication




Journal article


Diabetes Care

Publication Date





2424 - 2429


Adult, Body Mass Index, Fasting, Female, Glucose, Glucose Clamp Technique, Homeostasis, Humans, Insulin, Insulin Resistance, Kidney Transplantation, Male, Metabolic Syndrome, Middle Aged, Multivariate Analysis, Risk Factors, Triglycerides